Since the introduction of next-generation sequencing (NGS) technology, there has been a major transformation in the way researchers extract genetic information from biological systems, opening the way to expanded insight about the genome, transcriptome, and epigenome of any species. This ability has catalyzed a number of important breakthroughs, advancing fields from human disease research to agriculture and evolutionary science.
In principle, the concept behind NGS technology is similar to capillary electrophoresis (CE)-based Sanger sequencing: the bases of a small fragment of DNA are sequentially identified from signals emitted as each fragment is re-synthesized from a DNA template strand. (See, e.g., Metzker, M., Nature Biotechnology Reviews (2010) 11:31-46,which is incorporated herein by reference.) NGS extends this process across millions of reactions in a massively parallel fashion, without being limited to a single or a few DNA fragments. This advance enables rapid sequencing of large strings of DNA base pairs spanning entire genomes, with the latest instruments being capable of producing hundreds of gigabases of data in a single sequencing run. NGS differs from conventional Sanger sequencing in that in conventional Sanger sequencing, all copies of the DNA are sequenced together, while in NGS, the DNA is separated into small fragments that are isolated and individually sequenced. This distinction has implications in terms of procedures to enhance the sensitivity of the procedure for low-occurrence mutation detection.
With the advent of NGS, sequencing and testing for mutations has become a standard procedure in the diagnosis and management of patients with cancer. Screening for various mutations in cancer tissue provides a means for predicting prognosis and for determining therapy. Precision medicine and targeted therapy depends on the detection of molecular abnormalities and selecting therapy that target these molecular abnormalities. For example, the detection of EGFR mutation in a patient with cancer indicates that this patient most likely will respond to anti-EGFR kinase inhibitors. On the other hand, the detection of certain mutations may imply resistance to specific therapy. For example, the detection of the EGFR T790M mutation in a patient with cancer indicates that this patient will not respond to EGFR therapy.
Detection of mutations in specific genes is most commonly achieved using targeted tests that are designed to detect one or at least a small number of mutations in a single gene. NGS is gaining momentum as a complementary test for a number of reasons. Firstly, clinical trials for targeted cancer therapies rely on detection of mutations that are frequently not covered by existing targeted tests. Instead of relying on the slow and labor-intensive process of validating and implementing a new molecular assay to test for one or a few mutations, NGS simplifies the task of providing coverage of one or more additional mutations of interest. Second, targeted tests can provide misleading results, failing to identify therapeutically-targetable mutations. Further, targeted tests may fail to detect the very mutation they are designed to detect. Finally, tumors frequently harbor mutations that are therapeutically-targetable but are not typically seen in that tumor type. Due to its massively parallel nature, NGS is well suited for detecting mutations in unexpected genes.
Other technologies that have typically been used to measure minimal residual disease, like Sanger sequencing, cannot reliably detect mutations below 10 percent to 20 percent frequency. Experts agree that mutations present below 10 percent frequency are clinically significant, however, the appropriate threshold for defining a “significant” mutation requiring intervention has not yet been established. While NGS has provided a valuable tool for detecting mutations with a sensitivity in the range of 5 percent, it remains less sensitive for the detection of mutations that present in less than 5 percent of the analyzed DNA. This particularly becomes a problem when attempting to analyze peripheral blood plasma or other body fluids such as urine or bronchial lavage. Accordingly, the need remains for method for improving the sensitivity of NGS for purposes of detecting low-occurrence mutations.